The Impact of Dating Apps on the Mental Health of the LGBTIQA+ Population

Abstract

This study explores the psychological impact of dating app usage on the mental health of LGBTIQA+ individuals in Southeast Europe, focusing on key factors such as anxiety, cyberbullying, perceived security, and self-confidence. Data were collected through an online survey administered to a representative sample of active dating app users within the LGBTIQA+ community, enabling a comprehensive analysis of how these factors influence users’ emotional states, attitudes, and behavioral intentions related to dating app use. The findings reveal that, while dating apps provide important opportunities for social connection and support, they also pose significant risks. Cyberbullying was identified as a prominent issue, strongly associated with heightened anxiety, reduced self-confidence, and increased fear. Anxiety also showed a negative association with perceived security. Among the examined factors, fear and pleasure emerged as significant predictors of LGBTIQA+ users’ attitudes toward dating apps, which in turn influenced their intention to continue using them. The results underscore the need for enhanced security features and inclusive design practices that prioritize the psychological well-being of LGBTIQA+ users. By addressing these challenges, dating app developers and policymakers can create environments that support healthier interactions and promote more positive experiences for marginalized users.

1. Introduction

The internet has emerged as the primary communication tool of the 21st century, transforming daily interactions by enabling rapid information exchange across distances. According to DataReportal, 5.56 billion people worldwide were using the internet at the start of 2025, equivalent to 67.9% of the global population [1]. As internet usage continues to expand, online technology has significantly reshaped how individuals form and maintain relationships, influencing both friendships and romantic connections [2].

The increasing reliance on dating apps has redefined how people seek and establish relationships, particularly within the LGBTIQA+ community, which includes lesbian, gay, bisexual, transgender, intersex, queer/questioning, asexual individuals, and other identities outside of heterosexual and cisgender norms. Shilo and Mor [3] found that dating app usage surged during the COVID-19 pandemic, as social distancing measures forced individuals to rely on digital communication for intimacy and connection. This shift was accompanied by an increase in alternative forms of online intimacy, such as phone sex, webcams, and pornography consumption. Today, the online dating landscape is highly diverse, catering to various sexual orientations and gender identities. Blanc [4] reported that 38.5% of surveyed individuals ($n$ = 881) used dating apps, with Tinder being the most frequently used platform. Among these users, 57.2% exclusively used Tinder, while 88.9% combined Tinder with other dating apps such as Badoo, Meetic, Lovoo, and Grindr.

For LGBTIQA+ individuals, dating apps serve not only as a means of finding romantic or sexual partners but also as safe spaces for identity exploration and community building. Anderson et al. [5] reported that approximately 48% of individuals aged 18–29 and 55% of LGB adults have used a dating site or app, with 20% of these users entering committed relationships or marriages through online connections. Additionally, dating apps provide LGBTIQA+ individuals with opportunities to express their identities in ways they may not feel comfortable doing in face-to-face interactions [6]. Chan [7] found that the integration of LGBTQ+-focused social media into users’ daily lives was associated with lower levels of internalized stigma and higher levels of community connectedness, ultimately contributing to improved mental well-being.

Despite these benefits, online dating poses significant risks, particularly for LGBTIQA+ users. Several studies highlight the negative psychological consequences of dating app usage, including increased exposure to harassment, discrimination, and privacy violations. Echevarria et al. [8] found that Dating App Facilitated Sexual Violence (DAFSV) disproportionately affects sexual minorities and is linked to higher symptoms of depression, anxiety, loneliness, and reduced self-esteem. Privacy concerns further complicate the digital dating experience, particularly for marginalized groups. For instance, Grindr was found to have shared users’ HIV status with third-party companies without explicit consent, raising serious ethical and security concerns [9]. Lauckner et al. [10] demonstrated that discrimination, deception, and harassment are prevalent issues, particularly among rural sexual minorities, emphasizing the need for further research into the mental and sexual health implications of dating app usage.

Self-confidence plays a crucial role in the mental health of sexual and gender minorities. Studies have shown that higher levels of self-confidence are associated with lower internalized stigma, reduced symptoms of anxiety and depression, and overall improved well-being among LGBTIQA+ individuals. For instance, Meyer’s minority stress model [11] highlights how resilience factors, such as self-confidence, help mitigate the negative effects of discrimination and social exclusion. Furthermore, Puckett et al. [12] suggest that self-confidence serves as a protective factor against the psychological distress caused by cyberbullying and online harassment, common challenges faced by LGBTIQA+ individuals in digital dating environments. This underscores the necessity of exploring self-confidence within the context of online dating, particularly in relation to security perceptions, emotional well-being, and behavioral engagement.

Given the documented impact of self-confidence on mental well-being and resilience among LGBTIQA+ individuals, it is essential to examine how psychological theories can further explain these dynamics. To better understand how LGBTIQA+ users navigate these challenges, this study draws on established psychological theories. Stress and Coping Theory [13] explains how individuals evaluate and respond to stressors such as cyberbullying, privacy violations, and online harassment. Users engage in primary appraisal (assessing whether a stressor is harmful) and secondary appraisal (determining coping mechanisms). For LGBTIQA+ users, dating apps may serve as both sources of social connection and stress-inducing environments where negative experiences impact self-confidence and mental well-being. Protection Motivation Theory [14] provides a framework for understanding how perceived security risks influence online behaviors. Users assess threat severity (e.g., data privacy concerns, fear of harassment) and evaluate their ability to mitigate risks. This theory helps explain why some LGBTIQA+ users continue using dating apps despite safety concerns, while others disengage due to heightened fear and anxiety. The Affect Infusion Model [15] explains how emotions influence cognitive processing and decision-making. Negative emotional states, such as fear and anxiety, may lead to avoidance behaviors, while positive emotions like pleasure and enjoyment may encourage continued engagement with dating apps. By integrating these theoretical perspectives, this study examines how self-confidence, emotional responses, and security perceptions influence the behavioral engagement of LGBTIQA+ individuals with dating apps.

While existing studies have provided valuable insights into the psychological effects of dating app usage, they have not sufficiently explored the crucial links between self-confidence and mental health, an area this research aims to address. This study investigates how users’ self-confidence influences their emotional experiences, particularly mood, when using dating apps, and whether these experiences are shaped by high or low levels of self-confidence. Additionally, it examines the role of cyberbullying, security perceptions, and anxiety in shaping individuals’ self-confidence, further contributing to an understanding of how negative experiences impact users’ attitudes and behaviors.

Another key objective of this study is to explore how anxiety and fear influence security perceptions and users’ attitudes toward dating apps, as well as how these attitudes, in turn, shape behavioral intention. It also examines how perceived security affects user attitudes, and how cyberbullying contributes to fear responses in digital contexts. Through a comprehensive analysis of the literature, this research also assesses how stress affects users’ mood, how mood influences the pleasure derived from dating app use, and how this pleasure, in turn, shapes user attitudes. Lastly, this study examines how experiences of cyberbullying and fear responses influence anxiety levels among LGBTIQA+ individuals in digital environments.

To address these objectives, the study poses the following research questions:

• What is the association between anxiety and self-confidence, perceived security, and attitudes toward dating apps among LGBTIQA+ users?
• What is the role of cyberbullying and fear in shaping anxiety among LGBTIQA+ dating app users?
• How is fear associated with LGBTIQA+ users’ security perceptions and attitudes toward dating apps?
• How are cyberbullying and security perceptions associated with self-confidence among LGBTIQA+ dating app users?
• How do perceived security and pleasurable experiences shape attitudes toward dating apps among LGBTIQA+ users?
• How does exposure to cyberbullying contribute to fear in LGBTIQA+ users’ dating app interactions?
• How do stress and self-confidence affect the mood of LGBTIQA+ users while using dating apps?
• How is mood associated with LGBTIQA+ users’ sense of pleasure during dating app interactions?
• How do LGBTIQA+ users’ attitudes toward dating apps influence their intention to continue using them?

To investigate these research questions, this study employs a conceptual model that integrates psychological, behavioral, and security-related factors. A post-use questionnaire was developed to collect data from a representative sample of LGBTIQA+ dating app users in Southeast European countries. This approach enables capturing real-time psychological responses, ensuring robust empirical evidence. The validity and reliability of the model were assessed using partial least squares structural equation modeling (PLS-SEM).

This study makes several contributions. Conceptually, it integrates self-confidence, anxiety, cyberbullying, and security perceptions into a comprehensive framework explaining the psychological and behavioral consequences of dating app usage. Methodologically, by applying PLS-SEM to a region-specific sample of LGBTIQA+ dating app users in Southeast Europe, the research provides unique empirical insights into security perceptions and mental health risks. Practically, the findings will inform dating app developers, policymakers, and mental health professionals about designing safer, more inclusive platforms, specifically addressing privacy concerns, cyberbullying prevention, and user-centered security features.

The remainder of this paper is structured as follows: Section 2 provides a review of the existing literature on dating apps, self-confidence, and mental health among LGBTIQA+ individuals. Section 3 details the research methodology, including study design, data collection procedures, and analytical techniques. Section 4 presents the empirical findings derived from the data analysis. Section 5 discusses these findings in relation to existing research and theoretical perspectives. Section 6 outlines the practical and theoretical implications of the study. Section 7 highlights its limitations and suggests areas for future research. Finally, Section 8 concludes the paper by summarizing the key contributions and findings of the study.

2. Related Work

In this section, we undertake a review of existing empirical studies to provide a backdrop for our research and pinpoint areas where the current literature falls short.

The study conducted by Zervoulis et al. [16] using a cross-sectional questionnaire in the United Kingdom primarily addresses aspects of mood, self-confidence, and behavioral intention in relation to the reported impacts on sense of community, loneliness, life satisfaction, self-esteem, and the purposes for which gay dating apps (GDAs) are used. The findings show that GDAs affect men who have sex with men (MSM) particularly in terms of community and well-being, offering spaces for sexual expression and potential empowerment, but also emphasizing superficial sexual relationships and pressure to conform to app norms. Heavy users of GDAs report a lower sense of community, increased loneliness, and reduced life satisfaction. However, MSM who use GDAs primarily for sexual encounters report higher self-esteem and life satisfaction compared to those who use the apps for other purposes. This suggests that while GDAs effectively serve those seeking sexual partners, they may negatively affect users pursuing other types of relationships or interactions. The study highlights the dual nature of GDAs: they can provide emotional support and facilitate sexual expression, yet their focus on casual encounters may hinder the development of meaningful, intimate relationships.

Brown [17] investigated cyberbullying, fear, pleasure, attitude, self-confidence, and perceived security in the context of online harassment among LGB users. Although higher rates of harassment and threats were reported compared to heterosexual users, the findings also indicated a generally positive evaluation of online dating experiences within the LGB population. Survey results from the United States confirmed that LGB adults actively use dating platforms, reporting higher overall satisfaction than their heterosexual counterparts. These platforms were identified as particularly significant for individuals seeking same-sex relationships, offering broader access to potential partners. Despite disproportionate exposure to unwanted sexual content, derogatory language, and threats, LGB users consistently reported a stable perception of safety and enjoyment. This suggests a resilient engagement with digital dating environments, despite the persistence of discriminatory and hostile interactions.

The research carried out by Gelles-Watnick [18] on online dating within the LGB community primarily addresses aspects related to security. The study highlights the significant engagement of LGB Americans with online dating platforms, emphasizing the internet’s crucial role in fostering connections within the LGB community, especially when traditional avenues may be inaccessible. Across various age groups and genders, LGB adults exhibit a strong preference for apps like Tinder and Grindr, reflecting diverse needs and orientations. While 61% report overall positive experiences, a significant portion faces negative behaviors, including receiving unsolicited explicit messages (56%), and offensive name-calling (33%), with similar experiences across genders. Additionally, half suspects encounter scammers, particularly men. There is disagreement over the wider effects of online dating; 40% of respondents believe it makes finding a spouse easier, but opinions on how it affects relationships differ. The study also indicates that about 24% of partnered LGB adults met their significant other through online dating, with men more likely than women to report this mode of meeting. These findings underscore the complex world of online dating within the LGB community, where opportunities for connection and challenges such as harassment and scams persist.

Mussap et al. [19] uncovered that cyberbullying and non-consensual sexting significantly affect the mental well-being of 146 transgender, agender, and gender-diverse adults, particularly in relation to depression, anxiety, and stress. The aim was to understand how cyberbullying and non-consensual sexting affected the mental well-being of dating app users. Participants, ranging from 18 to 58 years old, shared their experiences and feelings, including levels of depression, anxiety, and stress. What emerged from the data was striking: cyberbullying and non-consensual sexting were significant factors contributing to feelings of being victimized, especially in terms of facing gender discrimination and rejection. The emotional toll of these experiences—particularly the feeling of being rejected based on gender identity—played a crucial role in intensifying psychological difficulties such as depression, anxiety, and stress. Surprisingly, there were no notable differences in these patterns based on how individuals identified their gender or presented themselves. However, it is essential to note that this study focused specifically on cyberbullying related to sexual matters, overlooking other forms of online mistreatment such as humiliation or attacks based on gender.

Marciano and Antebi-Gruszka [20] primarily addressed aspects of stress, anxiety, and self-confidence stemming from the psychological impact of discrimination based on participants’ weight, appearance, and age. Their research identified weight/body shape discrimination (36.5%) as the most prevalent on dating platforms, followed by general appearance (28.0%) and age (26.7%), underscoring the persistence of these factors as primary sources of bias in this context. Particularly noteworthy is the significant correlation found between weight/body shape discrimination and mental distress, alongside race, name, and gender expression, highlighting the distinctive impact of these characteristics on users’ psychological well-being. Additionally, the study revealed significant differences in discriminatory experiences based on demographic variables such as sexual orientation, gender identity, income, relationship status, and religion, emphasizing the need for targeted interventions and support systems. Younger participants reported more frequent experiences of discrimination, suggesting a generational component within the LGB community. Furthermore, discrimination was found to vary across digital spaces, with weight/body shape, political ideology, and appearance emerging as particularly prominent areas of concern.

While prior studies have examined various psychological and behavioral aspects of dating app usage among LGBTIQA+ individuals, most have focused on isolated constructs, such as anxiety, cyberbullying, security concerns, or self-confidence, without exploring their interconnections. Moreover, research on how cultural and contextual factors shape these experiences remains limited, particularly in regions with distinct socio-political climates, such as Southeast Europe. This study builds upon existing findings by integrating multiple psychological constructs into a unified framework and examining their relationships through a structural equation modeling approach. In doing so, it provides a more comprehensive understanding of how self-confidence, security perceptions, and negative digital experiences influence user attitudes and behaviors in online dating environments. The following section outlines the methodology employed to test these relationships empirically.

3. Research Methodology

Dating apps have become essential to contemporary social interactions, especially within the LGBTIQA+ community, providing platforms for connection and companionship. However, growing concerns surround their potential impact on users’ mental health, as issues such as cyberbullying, fear, anxiety, and stress emerge as key psychological challenges. Additionally, examining factors like mood, pleasure, self-confidence, and security can offer deeper insights into the complex dynamics between dating app usage and mental health outcomes. This study seeks to illuminate ways to promote user well-being, with a particular focus on the experiences of LGBTIQA+ individuals.

3.1. Constructs

The research model comprises a network of interrelated constructs, each representing distinct psychological and behavioral dimensions relevant to dating app usage, as described below. Anxiety (ANX) refers to irrational and negative anticipation that arises while using dating apps. Self-confidence (SE-CON) indicates the feeling of comfort with one’s physical appearance and age when using dating apps, as well as the impression they will have of others in real life. Security (SEC) denotes the sense of safety individuals experience while using the app, specifically regarding the protection of their identity. Cyberbullying (CYB) indicates the intentional and aggressive behavior of an individual while using dating apps to cause emotional pain to another user. Fear (FEAR) indicates a strong, negative, and uncomfortable feeling a person experiences when anticipating danger on dating apps. While fear and anxiety are both negative emotional responses, fear is typically a response to a perceived imminent threat, whereas anxiety is a more generalized and anticipatory feeling of unease that may not have a clear or immediate source. Mood (MOOD) refers to the emotional state of a person, which varies from positive to negative feelings when using dating apps. Mood represents a broader, more stable affective disposition that fluctuates over time and can be influenced by various factors, both external and internal. Attitude (ATT) indicates users’ subjective perspectives and beliefs about the meaningfulness and effectiveness of dating apps for creating connections and relationships. Stress (STRS) refers to emotional pressure or overload that occurs when using a dating app. Stress differs from anxiety in that stress is typically a response to external demands or pressures, whereas anxiety involves an internalized sense of worry or fear, often about uncertain outcomes. Pleasure (PLS) refers to a positive experience and pleasant emotions that users feel while using dating apps. Although mood and pleasure may appear similar, they measure distinct emotional dimensions. Mood is a general, long-lasting emotional state that can fluctuate between positive and negative, whereas pleasure is a more immediate, hedonic reaction to specific experiences on the platform. A user may have an overall negative mood when using the app but still experience pleasure from a particular interaction, or vice versa. Behavioral intention (BEH) presents the intention of users to continue using dating apps and recommend them to others.

3.2. Hypotheses

Goette et al. [21] found that stress significantly affects self-confidence, with individuals experiencing high levels of anxiety showing a marked decrease in self-confidence under stress compared to those with lower anxiety levels. Notably, in their study, they used a median split of trait anxiety scores, categorizing participants into high-anxiety ($n$ = 55) and low-anxiety ($n$ = 54) groups. These findings imply a connection between anxiety levels and self-confidence indicating that individuals with heightened anxiety may exhibit lower self-confidence, compared to those with lower anxiety levels. Additionally, Chorney and Morris [22] emphasized that individuals with elevated dating anxiety seek validation and demonstrate increased shyness in social situations. This suggests that users who are anxious about dating might use dating apps to feel good about themselves and talk to others more easily, compared to people who are not as nervous. In that respect, we propose the following hypothesis:

H1. 

Anxiety is negatively associated with self-confidence among LGBTIQA+ individuals using online dating apps.

Lutz and Ranzini [23] highlight that users of dating apps, such as Tinder, express significant concern over how companies manage their personal data, fearing misuse more than exposure to other users. This concern underscores a strong anxiety regarding the security of their information within the dating app. Complementing this, research by Farndenet et al. [24] highlights the technical vulnerabilities within dating apps, such as Grindr, that exacerbate privacy risks by sharing detailed user information, including unencrypted profile pictures and precise location data. This not only increases anxiety among users but also poses a distinct risk to marginalized communities, including LGBTIQA+ individuals, who may rely on these platforms for social connections while requiring a higher degree of anonymity for safety. Manning and Stern [25] further emphasize this point, noting that the spreading of personal data can particularly endanger those who depend on digital anonymity for their well-being. Thus, we propose the following hypothesis:

H2. 

Anxiety is negatively associated with perceived security in online dating apps used by LGBTIQA+ individuals.

Sumter and Vandenbosch [26] found that individuals experiencing high levels of dating anxiety are less inclined to engage with dating platforms, a behavior consistent with avoidance patterns observed among young adults faced with dating-related distress. This aligns with broader findings regarding technology apprehension. Rosen et al. [27] identified a specific factor in their study indicating a negative attitude toward technology, characterized by perceptions of it as time-wasting, socially isolating, and overly complex. These attitudes were inversely related to technology anxiety and dependence, suggesting that higher anxiety correlates with more negative views on technology use. Further supporting this notion, Korobili et al. [28] found a significant negative relationship between anxiety and attitudes toward technology among undergraduates, reinforcing the notion that anxiety—especially related to dating and technology—contributes to negative perceptions of dating apps. Collectively, these studies underscore the complex connection between anxiety and attitudes towards dating apps. Therefore, we propose the following hypothesis:

H3. 

Anxiety is negatively associated with attitude toward online dating apps among LGBTIQA+ users.

Dredge et al. [29] underscore the significant impact of cyberbullying on victims, linking it to severe outcomes including depression, anxiety, and suicidal ideation. This finding is corroborated by Carvalho et al. [30], who report that cyberbullying victims frequently suffer from a range of psychological issues, such as anxiety, depression, PTSD, and suicidal thoughts, indicating a profound effect on mental health. Moreover, Huang et al. [31] revealed a direct correlation between adolescent engagement with online dating platforms, experiences of online victimization, and negative psychological impacts, including anxiety. Schenk [32] further highlights the serious psychological consequences of cyberbullying, noting an increased prevalence of mental health conditions like depression, anxiety, and emotional distress among victims. Similarly, Kokkinos et al. [33] found that adolescents facing online harassment are at a greater risk of developing mental health problems, including anxiety and depression. Thus, we propose the following hypothesis:

H4. 

Cyberbullying is positively associated with anxiety related to online dating app use in the LGBTIQA+ population.

Corriero and Tong [34] claim that socially anxious users are concerned about their profiles being recognized by family and acquaintances, highlighting their fears about losing privacy and security. This fear is rooted in social anxiety tendencies, where individuals fear judgment and seek reassurance, as discussed by Cougle et al. [35], who link excessive reassurance seeking with social anxiety. Furthermore, Venkatesh and Davis [36] broaden the scope of this anxiety to technological interactions, positing that anxiety refers to fear over data loss or errors when utilizing technology. Thus, we propose the following hypothesis:

H5. 

Fear is positively associated with anxiety in online dating app interactions among LGBTIQA+ users.

A meta-analysis conducted by Tannenbaum et al. [37] revealed that fear appeals were successful at influencing attitudes, intentions, and behaviors across nearly all conditions that were analyzed, including cigarette smoking, breast self-examination, sunscreen usage, and medication adherence. Higher levels of fear generate systematic processing, which, in turn, leads to greater persuasion [38,39,40]. However, in the context of online dating within the LGBTIQA+ community, fear is primarily associated with concerns about privacy breaches, discrimination, and potential harm, which are well-documented barriers to engagement with digital platforms. Prior research has shown that heightened fear related to digital risks often leads to avoidance behaviors rather than increased adoption [41,42]. Given these factors, we hypothesize the following:

H6. 

Fear is negatively associated with attitude toward online dating apps within the LGBTIQA+ community.

Blomfield Neira and Barber [41] discuss how frequently social media usage can inversely affect self-esteem and mood, suggesting that an increase in the use of these platforms can lead to higher instances of depressed moods and poorer self-perceptions. Forgas [42] explores how mood influences the processing of self-confidence information, revealing that positive moods enhance the primacy effect, which elevates perceived self-confidence when positive traits are introduced first. Conversely, negative moods diminish this advantage and lead to a recency effect, where later information has a stronger influence on impression formation. This mutual relationship suggests that self-confidence can alleviate negative moods, but mood can also influence how self-confidence is perceived and formed. In that respect, we propose the following hypothesis:

H7. 

Self-confidence is positively associated with mood while using online dating apps among LGBTIQA+ individuals.

Chu et al. [43] found a significant correlation between cyberbullying victimization and adolescents’ psychosocial problems, highlighting how the experience of being bullied online can contribute to lower self-worth and social difficulties. This assertion is further confirmed by Baruah et al. [44], whose study revealed that a substantial majority of respondents involved in cyberbullying reported low levels of self-esteem. Conversely, only a small fraction reported medium levels of self-esteem, suggesting a strong association between cyberbullying involvement and decreased self-esteem among adolescents. Additionally, Tsaousis [45] indicates that lower levels of self-esteem are linked to higher risks of both bullying perpetration and victimization, reinforcing the notion that cyberbullying can detrimentally impact individuals’ self-confidence and overall psychological well-being. These findings collectively emphasize the harmful impact of cyberbullying on users’ self-perception and highlight the pressing need for interventions to alleviate the negative consequences of online harassment, particularly in digital environments such as dating apps. Thus, we propose the following hypothesis:

H8. 

Cyberbullying is negatively associated with self-confidence in LGBTIQA+ individuals using online dating apps.

Phan et al. [46] highlight the physiological and psychological effects that users may experience due to potential crimes such as stalking, fraud, and sexual abuse, which can lead to emotional distress and injury to self-esteem. Additionally, findings from a qualitative study by Cobb et al. [47] indicate that while some users express confidence in their ability to prevent security issues by being cautious with the information they share online, others feel vulnerable and anxious about potential security breaches. Participants who lack security concerns often attribute their confidence to having nothing to hide or feeling that their profiles contain relatively innocuous information. However, even seemingly basic personal details—such as age, ethnicity, or sexual position preferences—can pose risks if exploited maliciously, particularly within the LGBTIQA+ community, where such data may be used for doxxing, outing, targeted harassment, or discrimination. Prior research has documented cases where dating app data have been leveraged in blackmail schemes, social engineering attacks, and even police surveillance in regions where non-heteronormative identities are criminalized [48,49]. While some users mitigate these risks by providing false information, this practice is neither universal nor entirely protective, as behavioral patterns and metadata can still be used to infer sensitive attributes. This underscores the complex interplay between security considerations and users’ self-confidence in online dating environments. Therefore, we propose the following hypothesis:

H9. 

Security is positively associated with self-confidence in online dating apps for LGBTIQA+ users.

Breitschuh and Göretz [50] discovered that the fear of potential misuse of profile or chat data was one of the primary reasons users provide false information on dating apps, highlighting their anxiety regarding the security of their personal information. While the use of false information may serve as a protective strategy, it does not entirely mitigate the risks associated with online exposure. Users may still experience fear due to the possibility that their real identities could be uncovered through cross-referencing data, social engineering tactics, or platform vulnerabilities. Additionally, cyberstalking is characterized by intrusive and repetitive digital practices aimed at dominating victims’ intimate lives, with which they breach victims’ security. Even when users attempt to obscure their identity by providing misleading details, persistent cyberstalkers may exploit metadata, behavioral patterns, or linked accounts to circumvent these defensive measures. This contributes to heightened feelings of fear and vulnerability among users [51]. This form of harassment, which includes surveillance, threats, and identity theft, increases anxiety about online security. While some users may perceive that falsifying certain profile elements offers a degree of protection, the broader risk of being targeted remains, particularly when perpetrators engage in sustained digital tracking or manipulation. As a result, even individuals who employ deception as a safeguard may still experience fear regarding their safety and security on dating platforms. Thus, we propose the following hypothesis:

H10. 

Fear is negatively associated with perceived security in online dating apps among LGBTIQA+ individuals.

Privacy awareness plays a significant role in shaping how individuals feel about and perceive mobile apps. This influence extends to users’ attitudes towards these platforms, as highlighted by Li et al. [52]. Furthermore, awareness of threats and privacy concerns in the information technology environment significantly impacts users’ attitudes and intentions regarding the use of mobile apps and the sharing of personal information [53]. For instance, a study by Wottrich et al. [54] found that perceived privacy concerns negatively influenced users’ attitudes and decisions to use and grant app permission requests for accessing personal information. Thus, we propose the following hypothesis:

H11. 

Security is negatively associated with attitude toward online dating apps in the LGBTIQA+ population.

Consequences of cyberbullying often include significant psychological distress, with victims experiencing fear, discomfort, threat, anger, and sadness [55]. Despite the presence of online romantic interactions, adolescents and young adults exhibit a pervasive apprehension of dating violence and cyber abuse, yet they continue to use online platforms for dating and flirting, even amidst fears of violence and deception [56]. Studies have indicated that cyber-victimized individuals, particularly young women and those targeted by former partners, report heightened levels of fear, while men increasingly report fear when cyberstalking involves previous close relationships [57]. Threats and intimidation, common forms of cyberbullying, generate intense fear in victims, contributing to concerns about personal safety and well-being [58]. The nature of cyber-humiliation, which can occur through various online platforms at any time, exacerbates feelings of fear and the sense of being constantly monitored or tracked [59]. Thus, we propose the following hypothesis:

H12. 

Cyberbullying is positively associated with fear related to online dating app use in the LGBTIQA+ community.

Holtzhausen et al. [60] observed significantly higher levels of psychological distress and depression among dating app users, suggesting a correlation between dating app use and negative mood outcomes. Moreover, recent research indicates that stress can dysregulate dopamine, a neurotransmitter involved in mood regulation, potentially exacerbating mood disorders [61]. Dysregulation of the stress system has been documented in mood disorders, further highlighting the relationship between stress and negative mood states. Additionally, Kassel et al. [62] emphasize that stress often leads to negative mood states, which individuals typically find aversive. Thus, we propose the following hypothesis:

H13. 

Stress is negatively associated with mood while using online dating apps among LGBTIQA+ individuals.

Bonilla-Zorita et al. [63] found that better mood and self-esteem were associated with receiving notifications on dating apps, implying a positive correlation between app interactions and emotional well-being. Furthermore, pleasure, a crucial component of happiness, shares neural mechanisms with other pleasurable experiences such as socializing with friends [64]. Given these considerations, we put forward the following hypothesis:

H14. 

Mood is positively associated with pleasure in online dating app interactions in the LGBTIQA+ population.

Castañeda et al. [65] demonstrated a positive relationship between users’ positive experiences and their attitude toward technology, suggesting that enjoyable experiences contribute to favorable attitudes. Additionally, Luo [66] found that individuals perceiving the web as entertaining and informative tend to have a positive attitude towards it, supporting the notion that pleasure influences attitude. Furthermore, Finkel et al. [67] noted that greater experience with online dating can lead to more positive attitudes, emphasizing the role of user experience in shaping attitudes towards dating platforms. Thus, we propose the following hypothesis:

H15. 

Pleasure is positively associated with attitude toward online dating apps among LGBTIQA+ users.

Dwivedi et al. [68] highlighted a direct path from users’ attitudes to usage behavior, indicating that individuals with a positive attitude are more inclined to use information systems or technology. Bryant and Sheldon [69] also emphasized the significance of attitudes in determining the use of cyber dating apps, aligning with the theory of reasoned action. Additionally, Huang [70] found that subjective well-being strongly influences users’ intention to continue using technology. In that respect, we propose the following hypothesis:

H16. 

Attitude is positively associated with behavioral intention to use online dating apps among LGBTIQA+ individuals.

The conceptual model illustrating the interrelationships among the constructs in the form of hypotheses is presented in Figure 1. The proposed model was designed to capture the most theoretically and empirically relevant relationships within the context of LGBTIQA+ individuals using online dating apps. Certain linkages, such as the relationship between stress and anxiety, were not tested due to the study’s focus on more immediate predictors of self-confidence, security, and attitude. Prior research suggests that stress can directly contribute to anxiety in digital environments, particularly when triggered by cyberbullying. For instance, studies have shown that victims of cyberbullying report increased stress, which can lead to anxiety and depressive symptoms [71,72]. To maintain conceptual clarity and prevent overparameterization, only the most central pathways were included. This approach aligns with best practices in structural equation modeling, where parsimony is favored to enhance interpretability and reduce the risk of overfitting [73].

3.3. Procedure and Apparatus

For the purpose of data collection, a new questionnaire was developed. The constructs measured in the study were identified as a result of the literature review presented in Section 2. Although the target population consisted of individuals living in countries where the languages spoken are relatively similar, the survey instrument was formulated in English to ensure conceptual consistency and broader applicability of the findings.

The data were collected using an online survey via Google Forms from 17 July 2023 to 27 March 2024, targeting current LGBTIQA+ users of dating apps as respondents. Participants were primarily from Croatia, Bosnia and Herzegovina, and Serbia. We efficiently collected responses by distributing the questionnaire to LGBTIQA+ Discord channels and popular regional online communities serving these populations. We also engaged with several Facebook groups dedicated to sharing surveys and receiving responses to gather additional data. Furthermore, we received support from acquaintances and personally invited participants through face-to-face interactions.

The questionnaire comprised 5 items related to participants’ demography (age, sex, gender, sexuality, current country of residence); two items were designed to collect data on the time respondents spend on dating apps, along with five multiple-response items intended to gather information on the reasons for the app usage; one item for the names of frequently used apps; and four items aimed at understanding participants’ experiences and communications with other users, as well as their offline interactions with individuals they have met on dating apps.

The dimensions of the constructs comprising the proposed research model were measured using between 5 and 10 items: self-confidence (10 items), security (5 items), anxiety (8 items), mood (6 items), stress (6 items), fear (9 items), cyberbullying (6 items), attitude (8 items), pleasure (5 items), and behavioral intention (5 items). The items were worded by the first and second authors of the study to ensure alignment with the conceptual definitions of each construct. Responses to questionnaire items were modulated on a five-point Likert scale (1—strongly disagree, 5—strongly agree).

A statistical approach known as partial least squares structural equation modeling was applied to assess the reliability and validity of the research model and to examine the proposed relationships. Structural equation modeling (SEM) is a method for analyzing multivariate data, particularly for theory testing [74]. Partial least squares SEM (PLS-SEM) is a causal modeling technique focusing on maximizing the explained variance of dependent latent constructs rather than constructing a theoretical covariance matrix [75]. It is advantageous for exploratory research, handling complex models with small to medium sample sizes, and emphasizing prediction without imposing high data demands or requiring specified relationships [76,77]. PLS-SEM is especially useful when the research objective is predictive, making it popular in field of human–computer interaction. Researchers can model latent variables through their indicators and assess relationships even with measurement error. Using the inverse square root method proposed by Kock and Hadaya [78] and considering effect size ranges required for achieving 80% statistical power with the minimum path coefficient expected to be significant at the 5% level [73], our minimum required sample size was determined to be 138. With an actual sample size of 204, our study is considered statistically robust. The SmartPLS 4.1.0.0 software tool [79] was used to evaluate the psychometric properties of both the measurement and structural models. SmartPLS was chosen over other commercial PLS-SEM applications (such as WarpPLS and ADANCO) due to its robust analytical capabilities, intuitive interface, and comprehensive support resources, which together enabled rigorous analysis and modeling of complex relationships in this study.

4. Results

4.1. Study Participants

A total of 204 participants took part in the study, with 52.5% identifying as female, 46.6% as male, and 1% as another gender. Regarding sex, 44.1% identified as female, 42.6% as male, 4.9% as nonbinary, 4.4% as female-to-male (FTM) transgender, and 3.9% as male-to-female (MTF) transgender. The most common sexual orientation among participants was homosexual at 35.8%, followed by bisexual at 26.5%, queersexual at 14.7%, and pansexual at 8.3%. Additionally, 8.3% identified as asexual, 5.4% as heterosexual, 0.5% as polysexual, and 0.5% identified with other sexualities. It is important to note that participants who identified their sexuality as heterosexual are individuals who are transgender (FTM, MTF, nonbinary).

Most participants were from Croatia (42.2%), followed by Serbia (35.8%), Bosnia and Herzegovina (20.1%), Slovenia (1.5%), and Albania (0.5%). The age of respondents ranged from 18 to 38 (M = 24.27, SD = 3.666), with the majority (65.7%) being between 20 and 25 years old at the time the study was conducted.

When it comes to the daily usage of dating apps, 47.5% of participants use them for up to 1 h per day, and 46.1% spend 1–3 h per day on these platforms. A smaller group, 6.4%, use dating apps for 4–6 h daily. Notably, no participants reported using dating apps for 7–9 h or 10 or more hours per day.

In terms of frequency, 7.8% of participants use dating apps one time per week or less, while 32.8% use them two to three times per week. Additionally, 17.6% of participants use dating apps four to six times per week, and 22.1% use them once daily. Furthermore, 13.2% use dating apps two to four times per day, 3.9% engage with them five to seven times per day, and 2.5% use dating apps eight or more times per day.

Participants use dating apps for a variety of purposes. The most common use is chatting, with 132 participants (64.7%) engaging in this activity. Making friends is also popular, reported by 131 participants (64.2%), closely followed by dating, which is used by 119 participants (58.3%). Hooking up for sexual encounters is noted by 122 participants (59.8%), while finding a relationship partner is mentioned by 113 participants (55.4%). Networking is another significant use, with 93 participants (45.6%) indicating this purpose. Additionally, 82 participants (40.2%) use dating apps out of curiosity. A small number of participants, 2 (1%), use dating apps for other unspecified reasons.

Participants frequently use a variety of dating apps, with Tinder being the most popular, used by 139 participants (68.1%). Badoo follows, with 119 participants (58.3%) reporting usage. Grindr is used by 89 participants (43.6%), while OkCupid is used by 39 participants (19.1%). Romeo has 33 users (16.2%), and Hinge is used by 32 participants (15.7%). Bumble is mentioned by 24 participants (11.8%), and Bloom by 8 participants (3.9%). Less commonly used apps include Scruff with 2 users (1%), Iskrica with 1 user (0.5%), and Smokva, which is not used by any participants.

When asked how many times a person they agreed to meet did not show up, 47.5% of participants reported that this had never happened to them. Meanwhile, 34.3% experienced a no-show once, and 15.7% had this happen two to three times. A smaller percentage, 1.5%, reported four to five instances of no-shows, while 1% experienced more than five no-shows.

Regarding being ghosted by someone after making plans, 47.5% of participants stated it never occurred. However, 28.4% experienced ghosting once, and 19.1% reported it happening two to three times. Additionally, 3.4% faced ghosting four to five times, and 1.5% experienced it more than five times.

When asked about verbal insults during their first in-person meeting, most participants, 79.9%, reported never having experienced such an incident. However, 15.7% of participants indicated that they had been verbally insulted once. A smaller percentage, 3.4%, reported being insulted two to three times, while both 0.5% of participants experienced verbal insults four to five times and more than five times.

Regarding rejection during the first in-person meeting, 82.4% of participants stated they had never been rejected. However, 14.7% experienced rejection once, and 2.5% faced rejection two to three times. Notably, no participants reported being rejected four to five times, and only 0.5% experienced rejection more than five times.

In terms of experiencing setups or physical assaults by someone who met through a dating app, 92.6% of participants reported never having such an experience. A small percentage, 5.9%, had encountered this type of situation once. Very few participants, 0.5%, reported experiencing setups or physical assaults two to three times, four to five times, or more than five times.

The demographic characteristics of the study participants are collectively presented in

Table 1. Demographic profile of study participants.

Gender Identity	Percentage	Number of Participants
Female	52.5%	107
Male	46.6%	95
Other	1.0%	2
Sex
Female	44.1%	90
Male	42.6%	87
Nonbinary	4.9%	10
Female-to-Male (FTM) Transgender	4.4%	9
Male-to-Female (MTF) Transgender	3.9%	8
Sexual Orientation
Homosexual	35.8%	73
Bisexual	26.5%	54
Queersexual	14.7%	30
Pansexual	8.3%	17
Heterosexual	5.4%	11
Polysexual	0.5%	1
Other	0.5%	1
Nationality
Croatia	42.2%	86
Serbia	35.8%	73
Bosnia and Herzegovina	20.1%	41
Slovenia	1.5%	3
Albania	0.5%	1
Daily App Usage
Up to 1 h	47.5%	97
1–3 h	46.1%	94
4–6 h	6.4%	13
App Usage Frequency
Once a week or less	7.8%	16
2–3 times per week	32.8%	67
4–6 times per week	17.6%	36
Once daily	22.1%	45
2–4 times per day	13.2%	27
5–7 times per day	3.9%	8
8 or more times per day	2.5%	5
Purpose Of Usage
Chatting	64.7%	132
Making Friends	64.2%	131
Dating	58.3%	119
Hooking up	59.8%	122
Finding Relationship Partner	55.4%	113
Networking	45.6%	93
Curiosity	40.2%	82
Other	1.0%	2
Dating App Preferences
Tinder	68.1%	139
Badoo	58.3%	119
Grindr	43.6%	89
OkCupid	19.1%	39
Romeo	16.2%	33
Hinge	15.7%	32
Bumble	11.8%	24
Bloom	3.9%	8
Scruff	1.0%	2
Iskrica	0.5%	1
Smokva	0%	0
No-Shows Experience
Never	47.5%	97
Once	34.3%	70
2–3 times	15.7%	32
4–5 times	1.5%	3
Ghosting Experience
Never	47.5%	97
Once	28.4%	58
2–3 times	19.1%	39
4–5 times	3.4%	7
More than 5 times	1.5%	3
Verbal Insult Experience
Never	79.9%	163
Once	15.7%	32
2–3 times	3.4%	7
4–5 times	0.5%	1
More than 5 times	0.5%	1
Rejection Experience
Never	82.4%	168
Once	14.7%	30
2–3 times	2.5%	5
4–5 times	0%	0
More than 5 times	0.5%	1
Physical Assault/Setup Experience
Never	92.6%	189
Once	5.9%	12
2–3 times	0.5%	1
4–5 times	0.5%	1
More than 5 times	0.5%	1

.

4.2. Content and Construct Validity Evaluation

The evaluation of content validity was conducted using the closed card sorting method [80,81]. The content validity of the items was assessed through the content validity ratio (CVR) and the average relative importance of the items. To determine the CVR, ten raters assigned a relative importance score to each item on a three-point scale (1—essential, 2—desirable, 3—irrelevant) in relation to the construct to which they were allocated. Since it was necessary to consider items perceived by raters as either essential or desirable, the content validity ratio was calculated using a formula that excludes only those items deemed irrelevant by more than 50% of experts from further stages of measurement instrument development [82].

Items with a CVR value below 0.62—considered the reference value at a significance level of α = 0.05 for ten raters according to Lawshe [83]—as well as items with an average relative importance score above 2 were excluded from subsequent phases of the instrument development process.

An empirical criterion used to assess construct validity is the hit ratio, which indicates the extent to which raters correctly assigned items to the intended construct [84]. The hit ratio is calculated by dividing the total number of items correctly assigned to their respective constructs by all raters by the total number of possible item assignments across all raters. The overall hit ratio was 82%, which is considered acceptable given the lower acceptable threshold of 75% [84,85,86].

The reliability of results obtained through the closed card sorting method was measured using Conger’s Kappa coefficient of agreement [87]. The value of Conger’s Kappa coefficient was 0.885, indicating excellent inter-rater agreement. This procedure resulted in a final set of 68 items measuring the dimensions of ten constructs that constitute the research model.

4.3. Model Assessment

PLS-SEM estimates partial model structures by integrating principal component analysis with ordinary least squares regressions [73]. Thus, a two-stage evaluation of the psychometric features of the introduced conceptual model was undertaken. The quality of the measurement model was tested by examining the indicators’ reliability, internal consistency, convergent validity, and discriminant validity.

Indicator reliability was assessed by exploring the standardized loadings of items with their respective constructs. The analysis of cross-loadings and factor loadings evaluates how items correlate more strongly with their intended constructs than with other constructs, ensuring discriminant validity within the model. When items within a construct have strong loadings, it means they share common features captured by the construct, indicating reliability. According to Hair et al. [73], all item loadings should be significant and ideally exceed 0.708. Since the loadings of items SE-CON1, SE-CON4, SE-CON5, CYB2, CYB3, FEAR1, and FEAR2 were below the recommended threshold value, they were removed from the measurement model and further analysis. Additionally, items SEC3, ATT1, ATT3, ATT7, BEH3, PLS5, STRS1, STRS2, STRS3, and SEC-CON7 were removed because the convergent validity and internal consistency of the constructs were excessively high. The outcome of the confirmatory factor analysis (CFA) shown in

Table 2. Standardized factor loadings and cross-loadings of items.

	ANX	ATT	BEH	CYB	FEAR	MOOD	PLS	SE-CON	SEC	STRS
ANX1	0.792	−0.485	−0.445	0.539	0.533	−0.494	−0.499	−0.485	−0.394	0.589
ANX2	0.877	−0.557	−0.540	0.439	0.543	−0.623	−0.608	−0.590	−0.514	0.467
ANX3	0.826	−0.481	−0.450	0.437	0.584	−0.520	−0.499	−0.499	−0.426	0.508
ANX4	0.799	−0.497	−0.465	0.481	0.492	−0.574	−0.547	−0.558	−0.480	0.423
ANX5	0.893	−0.547	−0.535	0.466	0.584	−0.579	−0.580	−0.562	−0.556	0.465
ANX6	0.904	−0.570	−0.513	0.515	0.636	−0.539	−0.569	−0.593	−0.496	0.536
ANX7	0.804	−0.540	−0.511	0.570	0.592	−0.385	−0.556	−0.552	−0.321	0.629
ANX8	0.797	−0.468	−0.452	0.511	0.540	−0.329	−0.568	−0.522	−0.353	0.623
ATT2	−0.528	0.901	0.643	−0.545	−0.486	0.548	0.736	0.526	0.317	−0.362
ATT4	−0.512	0.801	0.525	−0.393	−0.560	0.486	0.632	0.446	0.394	−0.255
ATT5	−0.574	0.901	0.659	−0.546	−0.495	0.567	0.758	0.557	0.324	−0.395
ATT6	−0.541	0.877	0.632	−0.548	−0.444	0.575	0.688	0.543	0.310	−0.348
ATT8	−0.570	0.914	0.665	−0.554	−0.469	0.577	0.748	0.527	0.324	−0.359
BEH1	−0.455	0.548	0.847	−0.350	−0.299	0.467	0.621	0.414	0.255	−0.232
BEH2	−0.465	0.582	0.871	−0.312	−0.338	0.487	0.636	0.402	0.289	−0.178
BEH4	−0.579	0.714	0.939	−0.461	−0.439	0.582	0.800	0.530	0.378	−0.356
BEH5	−0.587	0.698	0.937	−0.467	−0.444	0.575	0.807	0.524	0.412	−0.367
CYB1	0.398	−0.359	−0.294	0.806	0.337	−0.238	−0.333	−0.257	−0.075	0.522
CYB4	0.388	−0.362	−0.290	0.787	0.324	−0.275	−0.333	−0.233	−0.114	0.439
CYB5	0.561	−0.546	−0.404	0.917	0.561	−0.408	−0.517	−0.444	−0.264	0.624
CYB6	0.573	−0.630	−0.465	0.853	0.574	−0.466	−0.624	−0.511	−0.344	0.522
FEAR3	0.577	−0.435	−0.315	0.470	0.890	−0.405	−0.428	−0.419	−0.367	0.418
FEAR4	0.600	−0.482	−0.389	0.464	0.935	−0.413	−0.467	−0.465	−0.394	0.455
FEAR5	0.625	−0.512	−0.416	0.497	0.935	−0.461	−0.491	−0.475	−0.385	0.442
FEAR6	0.581	−0.491	−0.352	0.475	0.804	−0.409	−0.510	−0.454	−0.273	0.528
FEAR7	0.481	−0.440	−0.367	0.453	0.753	−0.382	−0.438	−0.397	−0.323	0.322
FEAR8	0.555	−0.493	−0.376	0.442	0.781	−0.378	−0.520	−0.410	−0.307	0.527
FEAR9	0.595	−0.466	−0.348	0.556	0.870	−0.378	−0.443	−0.453	−0.342	0.563
MOOD1	−0.577	0.548	0.506	−0.436	−0.433	0.885	0.579	0.489	0.362	−0.327
MOOD2	−0.485	0.534	0.471	−0.386	−0.404	0.864	0.526	0.479	0.388	−0.298
MOOD3	−0.574	0.568	0.534	−0.385	−0.405	0.891	0.596	0.518	0.406	−0.271
MOOD4	−0.573	0.580	0.559	−0.428	−0.433	0.917	0.616	0.506	0.421	−0.303
MOOD5	−0.383	0.468	0.457	−0.212	−0.344	0.800	0.526	0.391	0.354	−0.098
MOOD6	−0.578	0.596	0.576	−0.412	−0.462	0.908	0.620	0.547	0.473	−0.273
PLS1	−0.600	0.766	0.713	−0.557	−0.514	0.574	0.921	0.556	0.389	−0.436
PLS2	−0.607	0.746	0.746	−0.543	−0.519	0.652	0.931	0.568	0.400	−0.430
PLS3	−0.569	0.689	0.726	−0.453	−0.439	0.540	0.871	0.523	0.358	−0.369
PLS4	−0.643	0.769	0.758	−0.515	−0.539	0.641	0.938	0.565	0.412	−0.407
SE-CON2	−0.533	0.527	0.376	−0.366	−0.453	0.444	0.503	0.809	0.377	−0.379
SE-CON3	−0.500	0.393	0.441	−0.341	−0.411	0.403	0.454	0.748	0.369	−0.384
SE-CON6	−0.578	0.489	0.461	−0.351	−0.499	0.438	0.533	0.852	0.469	−0.412
SE-CON8	−0.591	0.572	0.493	−0.464	−0.462	0.557	0.566	0.935	0.473	−0.413
SE-CON9	−0.611	0.549	0.487	−0.416	−0.414	0.540	0.548	0.916	0.487	−0.362
SE-CON10	−0.578	0.541	0.471	−0.438	−0.452	0.511	0.541	0.935	0.457	−0.383
SEC1	−0.507	0.343	0.359	−0.251	−0.364	0.418	0.388	0.463	0.966	−0.215
SEC2	−0.532	0.376	0.374	−0.270	−0.372	0.428	0.408	0.495	0.966	−0.243
SEC4	−0.390	0.285	0.282	−0.182	−0.373	0.403	0.345	0.405	0.770	−0.095
SEC5	−0.515	0.375	0.364	−0.262	−0.372	0.439	0.425	0.499	0.963	−0.228
STRS4	0.616	−0.380	−0.305	0.579	0.532	−0.301	−0.441	−0.403	−0.195	0.924
STRS5	0.565	−0.338	−0.268	0.592	0.511	−0.255	−0.375	−0.388	−0.204	0.923
STRS6	0.557	−0.367	−0.317	0.578	0.465	−0.277	−0.421	−0.442	−0.203	0.921

Note that bold values on the diagonal represent standardized factor loadings.

indicates that standardized loadings of all remaining items in the measurement model were above the acceptable cut-off level. Standardized loadings of items that constitute the measurement model are in the range from 0.748 to 0.966, which means that constructs accounted for between 55.95% and 93.32% of their items’ variance.

The internal consistency of constructs was evaluated through three key measures: Cronbach’s alpha, composite reliability (rho_C), and the consistent reliability coefficient (rho_A). Cronbach’s alpha [88] provides a conservative estimate of construct reliability, based on the assumption of equal weighting across items. Composite reliability [89], which considers actual item loadings, offers a more refined assessment of internal consistency than Cronbach’s alpha. Meanwhile, the consistent reliability coefficient by Dijkstra and Henseler [90] serves as an approximate exact reliability measure, striking a balance between Cronbach’s alpha and composite reliability [91]. For these metrics, values from 0.60 to 0.70 are generally acceptable in exploratory research, while values between 0.70 and 0.95 indicate robust internal consistency. Values exceeding 0.95, however, may suggest item redundancy, potentially compromising content validity [92]. As presented in

Table 3. Convergent validity and internal consistency of constructs.

Constructs	Cronbach’s Alpha	rho_A	rho_C	AVE
ANX	0.939	0.941	0.949	0.702
ATT	0.926	0.930	0.945	0.774
BEH	0.921	0.935	0.944	0.809
CYB	0.869	0.911	0.907	0.709
FEAR	0.937	0.940	0.950	0.731
MOOD	0.940	0.945	0.953	0.771
PLS	0.935	0.939	0.954	0.838
SE-CON	0.933	0.941	0.948	0.754
SEC	0.937	0.950	0.956	0.847
STRS	0.913	0.918	0.945	0.851

, the computed values for all three measures ranged between 0.869 and 0.956, demonstrating good internal consistency across the ten constructs within the research model. However, given that some reliability values approached the upper threshold of 0.95, raising concerns about potential item redundancy and artificially inflated correlations, it was necessary to assess whether common method variance (CMV) might be influencing the results. To examine this, Harman’s One-Factor Test was conducted using exploratory factor analysis (EFA) without rotation. The results indicated that the first extracted factor accounted for 44.804% of the total variance, which is below the commonly accepted threshold of 50% [93]. This suggests that common method bias is unlikely to pose a significant threat to the validity of the findings. Since Harman’s test did not indicate substantial common method variance, all items measuring the constructs were retained.

Convergent validity was evaluated through the average variance extracted (AVE), where a value of 0.50 or higher is considered adequate. This threshold signifies that the shared variance between a construct and its items exceeds the variance attributed to measurement error [91]. As shown in Table 3, the results confirm that all constructs in the research model meet this criterion.

Discriminant validity, indicating the degree to which each construct is distinct from others within the model, was assessed using the Heterotrait–Monotrait (HTMT) ratio of correlations [94]. This ratio is calculated as the mean of all correlations between indicators of different constructs divided by the mean of correlations between indicators of the same construct. Discriminant validity is considered unmet if the HTMT value exceeds 0.90 for related constructs and 0.85 for conceptually distinct constructs [92]. As shown in

Table 4. Heterotrait–Monotrait ratio of correlations (HTMT).

	ANX	ATT	BEH	CYB	FEAR	MOOD	PLS	SE-CON	SEC	STRS
ANX
ATT	0.664
BEH	0.623	0.763
CYB	0.630	0.620	0.473
FEAR	0.717	0.601	0.455	0.588
MOOD	0.638	0.669	0.629	0.447	0.503
PLS	0.705	0.870	0.858	0.590	0.588	0.699
SE-CON	0.697	0.635	0.561	0.471	0.554	0.592	0.647
SEC	0.562	0.407	0.399	0.258	0.431	0.489	0.455	0.542
STRS	0.683	0.424	0.342	0.698	0.589	0.321	0.483	0.486	0.230

, all constructs in the research model exhibit HTMT values below these respective thresholds, confirming that the discriminant validity criterion has been met, and that the constructs are adequately distinct. This evidence collectively reinforces the reliability and validity of the measurement model.

Following confirmation of the measurement model’s adequacy, the structural model’s suitability was assessed through several criteria: collinearity, path significance, coefficient of determination, effect size, and predictive power of the model.

Evaluating the structural model entails estimating multiple regression equations to represent the relationships between constructs. When two or more constructs in the structural model represent similar concepts, high collinearity may arise, potentially leading to biased estimates of partial regression coefficients. The Variance Inflation Factor (VIF) is a widely accepted metric for detecting collinearity among predictor constructs in the structural model. Although VIF values of 5 or above typically indicate collinearity issues among exogenous constructs, concerns may still arise with VIF values around 3 [91]. Thus, VIF values should ideally be close to or below 3. As displayed in

Table 5. Results of testing collinearity among exogenous constructs in the structural model.

	ANX	ATT	BEH	CYB	FEAR	MOOD	PLS	SE-CON	SEC	STRS
ANX		2.589						1.996	1.827
ATT			1.000
BEH
CYB	1.462				1.000			1.540
FEAR	1.462	1.900							1.827
MOOD							1.000
PLS		1.864
SE-CON						1.248
SEC		1.417						1.401
STRS						1.248

, VIF values for the predictor constructs range from 1.000 to 2.589, confirming the absence of collinearity within the structural model. Given that all VIF values are below the recommended threshold of 3.33, the model can also be considered free of common method bias [95].

The model’s explanatory power is evaluated through the coefficient of determination ($R^2$), which represents the proportion of variance in endogenous constructs explained by their predictors. Acceptable $R^2$ values vary depending on the research field and context [96]. In empirical studies evaluating social media, Orehovački [97] proposes that $R^2$ values of 0.15, 0.34, and 0.46 indicate weak, moderate, and substantial explanatory power of exogenous constructs within the research model, respectively. Adjusted $R^2$ is frequently applied as it adjusts for the size of the model, providing a more accurate measure of explanatory power [92]. The results presented in

Table 6. Results of testing the explanatory power of the research model.

Endogenous Constructs	${\mathit{R}}^2$	${\mathit{R}}^2$ Adjusted
ANX	0.518	0.513
ATT	0.679	0.672
BEH	0.508	0.505
FEAR	0.316	0.313
MOOD	0.316	0.309
PLS	0.434	0.431
SE-CON	0.473	0.465
SEC	0.286	0.279

indicate that 51.3% of the variance in anxiety is explained by cyberbullying and fear; anxiety, fear, security, and pleasure together account for 67.2% of the variance in attitude. Additionally, attitude explains 50.5% of the variance in behavioral intention, while 31.3% of the variance in fear is explained by cyberbullying. Self-confidence and stress contribute to 30.9% of the variance in mood which in turn accounts for 43.1% of the variance in pleasure. Furthermore, anxiety, cyberbullying, and security explain 46.5% of the variance in self-confidence, and 27.9% of the variance in security is explained by anxiety and fear. These findings indicate that the determinants of anxiety, attitude, behavioral intention, and self-confidence have substantial explanatory power, while the antecedent of pleasure demonstrate moderate explanatory power and the predictors of fear, mood, and security exhibit weak explanatory power.

The hypothesized relationships among constructs in the research model were assessed by examining path coefficients’ strength and direction. A bootstrapping resampling technique, using asymptotic two-tailed t-statistics, evaluated path significance with a sample size equivalent to the number of cases and 5000 bootstrap samples.

Table 7. Results of hypotheses testing.

Hypotheses	Path Coefficients	T Statistics	p Values	95% Confidence Intervals	Supported?
H1. ANX -> SE-CON	−0.451	6.808	0.000	[−0.575, −0.318]	Yes
H2. ANX -> SEC	−0.479	6.301	0.000	[−0.626, −0.330]	Yes
H3. ANX -> ATT	−0.089	1.429	0.153	[−0.210, 0.037]	No
H4. CYB -> ANX	0.308	5.271	0.000	[0.189, 0.419]	Yes
H5. FEAR -> ANX	0.499	10.735	0.000	[0.407, 0.592]	Yes
H6. FEAR -> ATT	−0.119	2.168	0.030	[−0.227, −0.013]	Yes
H7. SE-CON -> MOOD	0.529	8.384	0.000	[0.398, 0.646]	Yes
H8. CYB -> SE-CON	−0.131	2.303	0.021	[−0.243, −0.020]	Yes
H9. SEC -> SE-CON	0.233	3.706	0.000	[0.110, 0.361]	Yes
H10. FEAR -> SEC	−0.078	1.063	0.288	[−0.227, 0.071]	No
H11. SEC -> ATT	−0.014	0.278	0.781	[−0.108, 0.085]	No
H12. CYB -> FEAR	0.562	12.533	0.000	[0.474, 0.649]	Yes
H13. STRS -> MOOD	−0.066	1.058	0.290	[−0.192, 0.053]	No
H14. MOOD -> PLS	0.659	15.910	0.000	[0.574, 0.737]	Yes
H15. PLS -> ATT	0.693	12.291	0.000	[0.580, 0.802]	Yes
H16. ATT -> BEH	0.712	23.204	0.000	[0.649, 0.770]	Yes

details the hypothesis testing results, showing that anxiety (β = −0.451, p < 0.0001) and cyberbullying (β = −0.131, p < 0.05) significantly negatively influence self-confidence, while security (β = 0.233, p < 0.0001) positively impacts self-confidence, confirming H1, H8, and H9. Additionally, anxiety (β = −0.479, p < 0.0001) significantly negatively affects security, supporting H2, while fear’s negative impact on security (β = −0.078, p = 0.288) is non-significant, leading to the rejection of H10. Both anxiety (β = −0.089, p = 0.153) and security (β = −0.014, p = 0.781) had non-significant negative impacts on attitude, rejecting H3 and H11. Conversely, fear significantly negatively influences attitude (β = −0.119, p < 0.05), and pleasure has a strong positive effect on attitude (β = 0.693, p < 0.0001), supporting H6 and H15. Moreover, cyberbullying (β = 0.308, p < 0.0001) and fear (β = 0.499, p < 0.0001) positively affect anxiety, confirming H4 and H5. Self-confidence (β = 0.529, p < 0.0001) positively affects mood, supporting H7. On the other hand, stress (β = −0.066, p = 0.290) non-significantly negatively affects mood, leading to the rejection of H13. The results also show that cyberbullying (β = 0.562, p < 0.0001) is a significant predictor of fear, mood (β = 0.659, p < 0.0001) is a significant antecedent of pleasure, and attitude (β = 0.712, p < 0.0001) significantly influences behavioral intention, confirming H12, H14, and H16.

The effect size ($f^2$) quantifies the magnitude of influence exerted by an exogenous construct on an endogenous construct. Specifically, $f^2$ values of 0.02, 0.15, and 0.35 indicate small, medium, and large effects, respectively [98]. Referring to the $f^2$ values in

Table 8. Results of testing the effect size.

	ANX	ATT	BEH	CYB	FEAR	MOOD	PLS	SE-CON	SEC	STRS
ANX		0.010						0.193	0.176
ATT			1.031
BEH
CYB	0.135				0.462			0.021
FEAR	0.354	0.023							0.005
MOOD							0.766
PLS		0.802
SE-CON						0.328
SEC		0.000						0.074
STRS						0.005

, we interpret the relationships between the constructs for the proposed hypotheses as follows. Anxiety exerts a medium effect on both security ($f^2$ = 0.176) and on self-confidence ($f^2$ = 0.193). Attitude has a very large effect on behavioral intention ($f^2$ = 1.031). Cyberbullying significantly impacts fear ($f^2$ = 0.462), with a small influence on both anxiety ($f^2$ = 0.135) and self-confidence ($f^2$ = 0.021). Additionally, fear shows a substantial impact on anxiety ($f^2$ = 0.354) and a small impact on attitude ($f^2$ = 0.023). Mood was found to have a large effect on pleasure ($f^2$ = 0.766), which, in turn, significantly impacts attitude ($f^2$ = 0.802). Self-confidence demonstrated a medium effect on mood ($f^2$ = 0.328) while security showed a small impact on self-confidence ($f^2$ = 0.074). Given the rejection of hypotheses H3, H10, H11, and H13, the effects of anxiety on attitude ($f^2$ = 0.010), security on attitude ($f^2$ = 0.000), fear on security ($f^2$ = 0.005), and stress on mood ($f^2$ = 0.005) are negligible.

The model’s predictive power was assessed using the PLSpredict algorithm [99,100], which compares the model’s performance to a basic linear regression benchmark (denoted as ${\mathrm{Q}}_{\mathrm{p}\mathrm{r}\mathrm{e}\mathrm{d}\mathrm{i}\mathrm{c}\mathrm{t}}^2$ and defined by the indicator means from the analysis sample) [91,92,99]. PLS path models with ${\mathrm{Q}}_{\mathrm{p}\mathrm{r}\mathrm{e}\mathrm{d}\mathrm{i}\mathrm{c}\mathrm{t}}^2$ values above 0 demonstrate lower prediction errors relative to the simplest benchmark. Predictive power is generally evaluated using root mean squared error (RMSE). When prediction errors are highly asymmetric, however, the mean absolute error (MAE) is preferred [100]. This assessment involves comparing RMSE (or MAE) values to a baseline benchmark that predicts item values through a linear regression model (LM). The result of this comparison can be categorized as follows [100]: (a) RMSE (or MAE) values exceeding those of the naïve LM benchmark for all items indicate no predictive power; (b) higher prediction errors for the majority of endogenous construct items suggest low predictive power; (c) higher errors in a minority (or equal number) of construct items indicate medium predictive power; and (d) if no items show higher RMSE (or MAE) values than the LM benchmark, the model has high predictive power.

Visual inspection of the error histograms indicated a highly symmetric distribution of prediction errors, supporting the use of RMSE for predictive power assessment. As shown in

Table 9. Results of testing the predictive power of the research model.

	${\mathbf{Q}}_{\mathbf{p}\mathbf{r}\mathbf{e}\mathbf{d}\mathbf{i}\mathbf{c}\mathbf{t}}^{\mathbf{2}}$	PLS-SEM_RMSE	PLS-SEM_MAE	LM_RMSE	LM_MAE
ANX1	0.255	1.145	0.959	1.038	0.833
ANX2	0.185	1.159	0.930	1.094	0.872
ANX3	0.138	1.224	1.019	1.205	0.988
ANX4	0.219	0.813	0.558	0.804	0.568
ANX5	0.155	1.252	1.043	1.173	0.954
ANX6	0.207	1.403	1.172	1.362	1.061
ANX7	0.225	1.341	1.139	1.372	1.028
ANX8	0.209	1.387	1.161	1.355	0.988
ATT2	0.254	0.818	0.673	0.830	0.655
ATT4	0.059	0.985	0.803	1.075	0.891
ATT5	0.224	0.935	0.768	0.947	0.751
ATT6	0.216	0.886	0.759	0.938	0.752
ATT8	0.233	0.899	0.748	0.913	0.737
BEH1	0.110	1.003	0.838	1.051	0.843
BEH2	0.112	1.214	1.082	1.310	1.099
BEH4	0.190	1.136	0.941	1.072	0.843
BEH5	0.189	1.124	0.924	1.071	0.835
FEAR3	0.226	1.092	0.850	1.128	0.910
FEAR4	0.184	1.175	0.927	1.282	1.032
FEAR5	0.171	1.165	0.927	1.252	1.014
FEAR6	0.275	1.286	1.118	1.320	1.063
FEAR7	0.170	1.184	0.964	1.256	1.040
FEAR8	0.195	1.381	1.171	1.423	1.144
FEAR9	0.228	1.029	0.848	1.048	0.870
MOOD1	0.220	0.923	0.772	0.921	0.772
MOOD2	0.238	0.922	0.741	0.903	0.727
MOOD3	0.215	0.854	0.685	0.860	0.683
MOOD4	0.297	0.896	0.727	0.867	0.711
MOOD5	0.057	0.980	0.758	0.989	0.772
MOOD6	0.256	0.902	0.736	0.890	0.708
PLS1	0.306	0.864	0.728	0.788	0.628
PLS2	0.290	0.922	0.723	0.890	0.710
PLS3	0.201	1.017	0.815	1.007	0.809
PLS4	0.259	0.887	0.702	0.891	0.697
SE-CON2	0.133	1.302	1.082	1.367	1.083
SE-CON3	0.053	1.218	1.036	1.243	1.016
SE-CON6	0.090	0.976	0.816	1.013	0.787
SE-CON8	0.276	0.806	0.674	0.824	0.641
SE-CON9	0.223	0.871	0.697	0.929	0.731
SE-CON10	0.257	0.817	0.683	0.837	0.669
SEC1	0.039	1.283	1.105	1.362	1.165
SEC2	0.045	1.290	1.111	1.377	1.167
SEC4	0.023	1.050	0.852	1.075	0.890
SEC5	0.070	1.300	1.101	1.373	1.156

Note that bold values indicate that endogenous construct items have higher prediction errors in terms of RMSE or MAE when compared to the naïve LM benchmark.

, the majority of endogenous construct items displayed lower PLS-SEM RMSE values than the naïve LM RMSE benchmark, indicating medium predictive power for the proposed model.

4.4. Perceived Experiences on Dating Apps

In this subsection, only those items that met the reliability criteria during the evaluation of the research model will be interpreted. The analysis focuses on participants’ perceptions related to self-confidence, security, anxiety, mood, stress, fear, cyberbullying, attitude, pleasure, and behavioral intention concerning dating app usage.

The findings indicate that a substantial proportion of participants exhibit confidence in their self-representation on dating apps. Specifically, 62.3% of respondents feel comfortable posting pictures of their face, and 61.3% feel comfortable sharing images of their body. Furthermore, 61.7% of participants are at ease with how others perceive them both in real life and on dating apps. Authenticity in self-presentation is also evident, as 68.1% make an effort to provide accurate and genuine representations of themselves in their profile pictures. Moreover, honesty extends beyond visual presentation, with 74.1% of users reporting they are truthful about their age, interests, and characteristics, while 67.2% indicate they are transparent and sincere in their self-presentation.

Participants’ perceptions of security on dating apps reveal mixed responses. While 75.9% believe they have control over the visibility of their profile and personal details, trust in data protection is lower. Only 56.9% trust that dating apps do not share their information with third parties, and 55.4% believe their identity is protected. Additionally, only 53.9% feel safe from potential identity theft or fraud, indicating lingering concerns regarding personal data security.

Regarding anxiety levels, responses suggest that many users experience minimal emotional distress while using dating apps. A notable 83.8% strongly disagree with experiencing suicidal thoughts, and 68.7% disagree with feeling depressed when using these platforms. Similarly, 63.7% disagree with having negative thoughts, and 43.6% disagree with feeling disturbed. However, anxiety-related concerns persist for some, as 55.9% agree with fearing judgment and 55.4% express concerns about potential rejection.

The impact of dating apps on users’ mood appears predominantly positive. A significant 80.4% state that being matched with someone improves their day, while 77.4% report that receiving notifications elicits positive emotions. Additionally, 73.0% enjoy chatting on dating apps, and 67.6% note that messages received through these platforms enhance their mood. Moreover, 62.7% recognize a general mood-enhancing effect, and 57.3% state that frequent app usage improves their emotional state.

Stress associated with dating app usage primarily stems from social expectations. A substantial proportion of respondents (69.6%) feel pressured to meet high standards set by others. Similarly, 69.1% feel the need to create good impressions, and 58.9% believe they must conform to others’ expectations.

Concerns regarding safety and interactions with potentially harmful individuals are evident. A total of 69.6% of respondents express fear of encountering individuals who engage in bullying behavior. Additionally, 64.7% fear meeting a violent individual, while 64.2% are concerned about potential physical harm. Similarly, 63.8% worry about meeting someone with harmful intentions, and 61.3% fear unsafe encounters. Emotional harm (49.5%) and disappointment (48.5%) also emerge as notable concerns.

The findings highlight significant experiences of cyberbullying on dating apps. A notable 72.1% report having been victims of cyberbullying, while 69.1% have faced harassment due to their sexuality. Regarding humiliation, 42.2% agree they have experienced it, while 47.1% disagree. Additionally, 52.0% disagree with feeling intimidated by someone’s behavior on dating apps.

Attitudes toward dating apps exhibit moderate favorability. A total of 58.3% are open to meeting someone through these platforms, and 55.4% embrace forming new connections via dating apps. Additionally, 54.0% consider these platforms beneficial, and 48% view them positively.

Participants’ satisfaction with dating apps is relatively low. While 49.0% find them enjoyable, only 48.0% agree that these apps meet their expectations. Similarly, 47.6% report a positive overall impression, and 46.1% state that the outcomes of their experiences exceeded expectations.

Despite mixed attitudes and experiences, behavioral intention toward continued usage remains strong. A considerable 74.1% intend to continue using dating apps, while 58.4% plan to do so regularly. Furthermore, 54.0% would recommend dating apps to those seeking new social connections, and 53.9% would endorse them to friends and acquaintances.

A complete list of all items, along with their mean values, is provided in

Table A1. Perceived experiences on dating apps.

Items	Mean	SD
Self-confidence (SE-CON)
SE-CON1. I post pictures that highlight my physical imperfections on dating apps.	3.04	1.386
SE-CON2. I feel comfortable posting pictures of my face on dating apps.	3.65	1.322
SE-CON3. I feel comfortable posting pictures of my body on dating apps.	3.65	1.295
SE-CON4. I compare my body and face with other users’ bodies and faces on dating apps.	4.16	1.246
SE-CON5. I feel confident about my age when using dating apps.	4.02	1.125
SE-CON6. I am comfortable with how others perceive me in real life and on dating apps.	3.73	1.093
SE-CON7. I strive to portray an authentic version of myself in my dating app profile.	3.97	0.964
SE-CON8. I make an effort to provide accurate and genuine representations of myself in photos on dating apps.	3.94	0.958
SE-CON9. I am honest about my age, interests, and characteristics in my dating app profile.	4.07	0.980
SE-CON10. I am transparent and sincere when presenting myself on dating apps.	3.95	0.986
Security (SEC)
SEC1. I trust that the dating app does not share my information with third parties.	3.53	1.340
SEC2. I believe that dating app protects my identity.	3.49	1.363
SEC3. I trust that my personal information is secure while using the app.	3.55	1.376
SEC4. I have control over the visibility of my profile and personal details on the app.	4.24	1.044
SEC5. I feel safe from potential identity theft or fraud while using the app.	3.48	1.363
Anxiety (ANX)
ANX1. When using dating apps, I feel disturbed.	2.86	1.269
ANX2. When using dating apps, I feel depressed.	2.16	1.274
ANX3. When using dating apps, I feel concerned.	2.50	1.300
ANX4. I have suicidal thoughts when using dating apps.	1.63	0.992
ANX5. I have bad thoughts when using dating apps.	2.27	1.299
ANX6. I anticipate negative outcomes while using dating apps.	2.76	1.447
ANX7. I am afraid of being judged on dating apps.	3.44	1.425
ANX8. I am afraid of being rejected on dating apps.	3.37	1.488
Mood (MOOD)
MOOD1. Messages from dating apps have a positive impact on mood.	3.84	1.021
MOOD2. I feel good when chatting on dating apps.	3.95	0.999
MOOD3. I feel good when I receive a notification from dating apps.	4.10	0.931
MOOD4. Dating apps have a positive effect on my mood.	3.77	1.069
MOOD5. Being matched with someone on a dating app makes my day.	4.10	0.988
MOOD6. Using dating apps often improves my mood.	3.71	1.055
Stress (STRS)
STRS1. When using dating applications, I feel stressed.	2.60	1.391
STRS2. When using dating applications, I am under pressure.	2.59	1.381
STRS3. When using dating applications, I am constantly in some kind of anticipation.	2.67	1.392
STRS4. When using dating applications, I believe I need to meet others’ expectations.	3.50	1.315
STRS5. When using dating applications, I feel I have to make good impressions.	3.88	1.169
STRS6. When using dating applications, I need to meet the high standards set by others.	3.95	1.169
Fear (FEAR)
FEAR1. I’m afraid I might come across someone I know while using the app.	2.95	1.698
FEAR2. I’m afraid that someone I’m chatting with is catfishing me.	3.90	1.159
FEAR3. The possibility of encountering an unsafe individual on dating apps makes me feel scared.	3.58	1.312
FEAR4. I’m afraid I will encounter someone who is violent.	3.63	1.342
FEAR5. I’m afraid I will meet someone who wants to harm me.	3.62	1.347
FEAR6. I’m afraid I will meet someone who will disappoint me.	3.04	1.555
FEAR7. I’m afraid I will meet someone who will physically hurt me.	3.65	1.380
FEAR8. I’m afraid I will meet someone who will emotionally hurt me.	3.18	1.548
FEAR9. I’m afraid I will come across someone who enjoys bullying people.	3.80	1.245
Cyberbullying (CYB)
CYB1. I was a victim of cyberbullying while using dating apps.	3.89	1.707
CYB2. I experienced cyberbullying on dating apps more than once.	2.20	1.760
CYB3. I was cyberbullied on dating apps because of my gender.	1.89	1.595
CYB4. I was harassed on dating apps because of my sexuality.	3.78	1.774
CYB5. I have been humiliated on dating apps.	2.90	1.538
CYB6. I have felt intimidated by someone’s behavior on a dating app.	2.72	1.536
Attitude (ATT)
ATT1. I have a positive opinion about meeting people through dating apps.	3.50	1.029
ATT2. I think it’s a good idea to meet someone through a dating app.	3.46	0.954
ATT3. I like the idea of meeting someone through a dating app.	3.48	1.076
ATT4. I hold a favorable attitude toward meeting people through dating apps.	3.34	1.050
ATT5. I believe it is a beneficial concept to connect with others through dating apps.	3.48	1.048
ATT6. I am open to the idea of meeting someone through a dating app.	3.69	1.011
ATT7. I view meeting people through dating apps as a positive opportunity.	3.63	0.945
ATT8. I embrace the possibility of forming connections through dating apps.	3.62	0.987
Pleasure (PLS)
PLS1. Dating apps have met my expectations.	3.42	1.063
PLS2. The dating apps have left a good impression on me.	3.36	1.094
PLS3. The outcomes of using dating apps have been better than I expected.	3.30	1.177
PLS4. I find it enjoyable to use dating apps.	3.46	1.052
PLS5. I am satisfied with the dating apps I have used.	3.61	1.028
Behavioral Intention (BEH)
BEH1. I intend to continue using dating apps.	4.04	1.014
BEH2. I will continue using dating apps regularly.	3.54	1.196
BEH3. I will use dating apps often.	3.53	1.209
BEH4. I would recommend using dating apps to everyone who wants to meet new people.	3.65	1.171
BEH5. I would recommend using dating apps to my friends and acquaintances.	3.61	1.197

Note that the items in italics have been excluded from the research model as they did not meet the required reliability criteria.

in the Appendix A.

Figure 2 illustrates the average proportion of positive responses across psychological and experiential constructs related to dating app use among LGBTIQA+ individuals. The results indicate meaningful variation in users’ experiences and emotional responses.

The Mood construct shows the highest proportion of positive responses (69.7%), indicating that dating apps often serve as emotionally affirming environments. For users who may face marginalization or limited visibility in offline contexts, these platforms offer opportunities for validation, belonging, and uplifting interpersonal interactions—however brief or casual they may be.

Self-Confidence, with a high average (65.8%), suggests that users are generally comfortable with how they present themselves online. Within the LGBTIQA+ community, this is particularly meaningful, as dating apps can offer a rare space where authenticity is not only possible but sometimes safer or more rewarding than in face-to-face settings. The results may reflect users’ efforts to claim and communicate identity on their own terms.

The elevated prevalence of Cyberbullying (61.1%) highlights persistent exposure to targeted hostility, likely reflecting homophobia, transphobia, or other forms of identity-based discrimination. This underscores the dual nature of dating platforms—as both spaces of visibility and sites of vulnerability—where social interaction is coupled with the risk of victimization.

Security, with a moderate average (60.5%), reflects a nuanced perception of digital safety. While users may feel some control over how much of themselves they disclose, trust in platforms’ ability to protect sensitive data remains limited. For individuals whose identities are politicized or criminalized in certain contexts, this lack of trust may carry serious emotional and even physical consequences.

Despite these concerns, Behavioral Intention remains relatively high (60.1%), suggesting that users are willing to continue engaging with dating apps. This may reflect a lack of accessible offline alternatives for meeting like-minded individuals, or a strategic use of digital spaces to overcome geographical or social isolation.

The construct of Anxiety (59.2%) indicates that most users do not experience severe distress when using dating apps, but emotional ambivalence is still present. Fear of rejection or judgment may be especially heightened for those whose identities are often misunderstood or fetishized, adding complexity to otherwise positive emotional outcomes.

A moderate score for Attitude (54.0%) reflects a cautious openness to these platforms. While many recognize their potential, skepticism likely arises from prior negative experiences or systemic barriers within app culture—such as algorithmic bias or exclusionary design.

Pleasure, with a relatively low average (47.7%), suggests that emotional satisfaction does not always follow usage. This may point to a disconnect between the promise of connection and the reality of app dynamics, especially when interactions are superficial, transactional, or invalidating.

Fear (reverse-coded, 39.7%) captures deep-seated concerns regarding harmful encounters. These include fear of physical violence, emotional manipulation, or being “outed” in unsafe environments—concerns that are often heightened for LGBTIQA+ individuals navigating public and private boundaries.

Stress shows the lowest average (34.1%, reverse-coded), suggesting significant pressure to conform, impress, or perform. This may stem not only from general social norms but also from internalized stigma, hypervisibility, or the need to manage others’ perceptions of gender and sexuality in highly codified digital environments.

For LGBTIQA+ users, dating apps function as complex digital ecosystems—providing connection, visibility, and affirmation, but also exposing individuals to social, emotional, and safety-related risks. The findings reveal a tension between the emotional rewards of engagement and the psychological costs of navigating identity in spaces that are not always inclusive or protective. Enhancing safety, representation, and the quality of interaction remains essential if dating apps are to serve as sustainable tools for LGBTIQA+ connection and well-being.

5. Discussion

Study findings indicate that anxiety is associated with self-perception and social interactions among dating app users, with particularly pronounced effects observed within marginalized communities, such as the LGBTIQA+ group. Within these digital spaces, where self-presentation is paramount, anxiety often correlates with lower self-confidence [101]. Users, particularly those already navigating identity-based pressures, approach profile creation and interactions with heightened caution, acutely aware of the potential for judgment. This careful self-monitoring, while intended to protect against negative perceptions, is often linked to diminished self-confidence. By placing too much weight on how they might be received, anxious users may hesitate to engage fully, limiting their ability to derive meaningful social benefits from these platforms. This phenomenon highlights the dual effect of anxiety: it is associated with both a more cautious approach to self-presentation and a reduced likelihood of forming genuine connections.

In addition to its link with self-confidence, anxiety is also associated with how users perceive security on dating apps. For those particularly concerned with privacy, the sense of safety can feel fragile, and users prone to anxiety tend to view these platforms as more vulnerable to privacy threats [102]. LGBTIQA+ users, often wary of identity exposure, may experience security as foundational to their comfort, meaning even small security lapses can create a sense of instability. Anxiety appears to amplify this sensitivity, prompting users to scrutinize their digital environment more critically, with perceived security risks sometimes outweighing even the most robust protection measures in place. As a result, for these users, the perceived integrity of the platform’s security practices holds as much weight as actual technical protections.

Despite anxiety’s associations with self-confidence and perceived security, it does not necessarily lead to an overall negative view of dating apps. For many users—especially those within the LGBTIQA+ community—dating platforms serve as essential spaces for social engagement and self-exploration [103]. These platforms offer unique opportunities to connect, and the potential for meaningful social interaction may counterbalance momentary anxieties tied to specific interactions. This nuanced response suggests that users differentiate between episodic stress and the overall purpose these apps fulfill in their social lives. By compartmentalizing situational anxieties, users manage to maintain a constructive perspective on dating apps, viewing them as beneficial spaces despite any challenges that might arise in particular moments.

However, the issue of cyberbullying introduces unique complexities, particularly given dating apps’ intimate nature. Here, harassment is not just damaging but also intrudes upon deeply personal aspects of users’ identities, which can have lasting effects on their well-being. For LGBTIQA+ users, cyberbullying often targets core aspects of identity, reinforcing pre-existing fears about acceptance. The anonymous nature of such interactions emboldens perpetrators and leaves victims with limited recourse, intensifying feelings of helplessness [104]. This anticipatory anxiety—where users expect negative interactions at any time—has been associated with emotional exhaustion, discouraging engagement and potentially impacting mental health. Cyberbullying’s reach extends beyond immediate distress, manifesting as ongoing social withdrawal and reinforcing fears that may shape offline interactions as well.

Fear, as a broader psychological factor, also appears to shape users’ experiences on dating apps, amplifying anxieties and influencing their behavior patterns. Unlike anxiety, which can fluctuate, fear may function as a more continuous influence, affecting how users navigate potential rejection, judgment, or privacy concerns. LGBTIQA+ users, in particular, report experiencing this fear in connection with identity disclosure. When trust in the app’s ability to safeguard personal information is uncertain, users engage with increased caution, potentially limiting their ability to connect and diminishing the social value of these platforms [105]. Fear thus appears to function as a psychological barrier, prompting users to retreat into defensive behavior, which can hinder the formation of connections that dating apps are designed to facilitate.

This deep-seated fear is also associated with more negative attitudes toward dating apps overall. For individuals who experience heightened fear, dating apps may be perceived as less supportive social spaces and more as environments filled with risk [106]. This sentiment is particularly strong among LGBTIQA+ users, for whom exposure carries the threat of discrimination or harassment. Over time, such negative perceptions may contribute to reduced engagement, further isolating users and diminishing the app’s potential role as a bridge to community and social affirmation.

On the other end of the spectrum, self-confidence appears to function as a stabilizing factor that may mitigate some of these negative effects. Users with higher self-confidence tend to approach dating apps with greater assurance, which is linked to a more open and positive approach to interactions [107]. They are more likely to view interactions favorably, seeing them as opportunities to connect rather than as judgments on their character. For LGBTIQA+ users, this confidence is associated with more authentic self-expression and resilience against potential setbacks. With a positive self-view, users may derive greater satisfaction from their interactions, navigating these platforms with less apprehension and greater emotional stability.

Conversely, cyberbullying is particularly associated with reductions in self-confidence, especially for individuals whose identities are often the target of online harassment. The personal nature of these interactions leaves little room for psychological distance, and victims may internalize hostile messages [108]. For LGBTIQA+ users, whose identities may already be vulnerable to societal prejudice, cyberbullying is linked to diminished self-worth and a reluctance to engage authentically. This cycle of declining self-confidence not only influences users’ digital behaviors but may also have broader implications for their mental health and self-perception beyond the app environment.

Perceptions of security further influence users’ willingness to participate on dating apps, with personal data protection standing as a critical factor in fostering self-confidence. For LGBTIQA+ users, perceived security is associated with a greater sense of control, particularly regarding identity protection. When security is perceived as robust, users tend to engage with greater confidence, trusting that their information will remain private. This perceived safety is linked to more open interactions, increasing the platform’s effectiveness as a social space. However, without clear assurances of security, users may restrict their engagement, feeling that the risks associated with identity exposure outweigh the app’s potential benefits [109].

Fear and perceived security do not always correlate directly; users appear to differentiate between fears related to specific social interactions and their overall sense of platform safety [110]. This compartmentalization suggests a nuanced psychological response, where users feel secure in terms of data privacy yet may still experience situational apprehensions. For LGBTIQA+ users, who balance concerns about identity with trust in data protections, this distinction may facilitate a more adaptive approach, enabling them to interact confidently while managing specific fears.

Security, though foundational, does not independently create positive attitudes toward dating apps. Many users regard security as a baseline requirement rather than an enhancement to their experience [111]. Instead, positive attitudes appear to be more strongly associated with the quality of social connections facilitated by the app. For dating platforms, this underscores the importance of not only providing robust security but also fostering an inclusive environment that supports genuine, meaningful interactions.

Cyberbullying’s impact on fear is notable, as it appears to contribute to anticipatory anxiety and a diminished sense of safety within these digital environments. Victims, especially LGBTIQA+ users, often develop heightened vigilance, anticipating negative encounters that may reduce their engagement. This persistent alertness undermines users’ ability to enjoy the app, reinforcing isolation and limiting its potential as a social space [112]. Such dynamics highlight the need for stronger anti-bullying measures to restore trust and inclusivity on these platforms.

Not all stress on dating apps is detrimental; some users experience eustress, a positive form of stress that enhances their engagement and excitement. Those who view dating apps as a low-stakes environment interpret challenges like delayed responses or ambiguous signals as manageable, framing them as part of the dating process rather than as significant obstacles [113,114]. This adaptable approach enables users to engage with the platform in a balanced way, deriving enjoyment from the process rather than being weighed down by minor setbacks.

Positive mood further enhances users’ pleasure, as individuals who approach interactions with optimism are more likely to interpret messages favorably and sustain engagement. For LGBTIQA+ users, a positive mood supports authenticity, allowing them to connect without concerns of judgment. This connection between mood and pleasure suggests that a constructive emotional outlook is linked to user satisfaction and fulfillment in social exchanges on the app [115].

Pleasure also appears to underpin positive attitudes toward dating apps, as users who find it in interactions tend to appreciate and recommend the platform [116]. For many LGBTIQA+ users, these apps are often perceived as essential social resources, reinforcing a sense of community and validation. Pleasure may drive users to overlook occasional frustrations, fostering resilience and supporting a lasting, favorable view of the app.

Finally, positive attitudes are strongly associated with continued usage and recommendations, as users who view dating apps favorably tend to stay active and share the platform with others [117]. For LGBTIQA+ users, these platforms are often perceived as crucial for identity exploration and connection, and engagement within these spaces is linked to the development of a supportive, inclusive community that reinforces the app’s perceived value.

6. Implications

The findings of this study present several significant implications, particularly for developers of dating apps and researchers focused on digital behaviors and mental health within the LGBTIQA+ community.

For developers, one key implication is the need to enhance security measures to address user concerns around privacy and data safety. The study underscores how user anxiety strongly impacts perceived security and self-confidence, suggesting that improving data protection protocols could alleviate anxieties associated with data misuse. Robust privacy measures, such as end-to-end encryption, clearer data-sharing policies, and customizable privacy settings, can empower users by providing them with greater control over their personal information. This, in turn, may increase users’ sense of security and confidence, leading to more positive and engaged interactions on the platform.

The study also highlights the significant psychological toll of cyberbullying, particularly its association with increased levels of anxiety and fear. To create a safer environment, dating app developers should consider implementing advanced detection systems for abusive behavior, easy-to-use reporting tools, and accessible mental health resources. For example, apps could include automated filters that flag potentially harmful language or provide users with options to immediately report harassment. Additionally, integrating mental health support or links to relevant services could offer relief to users who experience online bullying. By prioritizing anti-harassment measures, developers can reduce the negative mental health impacts of cyberbullying, encouraging more positive and meaningful engagement on their platforms.

Moreover, the study’s findings indicate that mood and self-confidence contribute to users’ emotional enjoyment of dating app use, which in turn positively shapes their attitudes. These results suggest that emotionally supportive and inclusive design features—particularly those enhancing confidence and well-being—may indirectly foster more favorable user engagement. For instance, providing customization options that allow users to express their identities authentically—such as detailed gender identity, pronoun, and orientation fields—can create a more inclusive atmosphere. Promoting positive interactions and enjoyable experiences, such as personalized notifications or community-driven activities, can foster an emotionally safe space that supports users’ self-confidence and well-being. By adopting a user-centered approach that considers emotional health, apps can cultivate an environment where LGBTIQA+ users feel both safe and valued.

For researchers, these findings emphasize the importance of studying the psychological factors that shape user behavior in digital environments. This study reveals how variables like anxiety, fear, and self-confidence play a crucial role in technology adoption and sustained engagement, particularly among vulnerable user groups. Understanding these psychological influences provides a deeper perspective on how mental health factors impact user experiences and informs strategies to improve digital engagement in ways that prioritize user well-being.

The study also suggests that cultural and contextual factors may influence how users perceive security risks and respond emotionally to digital interactions. For instance, the non-significant relationship between fear and perceived security may reflect specific cultural or regional influences among the study’s sample of LGBTIQA+ users from Croatia, Serbia, and Bosnia and Herzegovina. In these societies, historical experiences with digital privacy violations, government surveillance, and data misuse might contribute to a general skepticism toward online security, potentially weakening the expected association between fear and perceived security. The legacy of political instability and concerns over data protection, particularly in relation to personal identity and surveillance, could mean that users do not necessarily link their immediate fears with the perceived security of a dating app. Instead, they may view digital privacy as an overarching concern that extends beyond individual platforms. Additionally, prevailing social attitudes toward the LGBTIQA+ community in this region may shape users’ coping mechanisms, leading some individuals to downplay security concerns in favor of prioritizing social connection. In societies where LGBTIQA+ individuals face discrimination or lack of institutional protection, online spaces often serve as critical avenues for self-expression, community support, and romantic or social interactions. This could result in users developing a sense of resilience or normalization of security risks, where the need for connection outweighs concerns about digital safety. Moreover, the collective nature of some LGBTIQA+ support networks in these countries may foster a communal approach to risk management, where users rely on word-of-mouth guidance or closed online communities rather than individual assessments of security measures provided by dating apps. Researchers may wish to explore how these variables manifest across different cultural contexts, potentially uncovering unique insights into the global experiences of LGBTIQA+ users. Future studies could examine whether similar patterns emerge in other regions with histories of digital surveillance or social marginalization of LGBTIQA+ individuals, providing a broader perspective on how cultural backgrounds shape digital risk perceptions and behaviors.

Furthermore, the findings provide a foundation for developing targeted interventions that address the specific mental health needs of LGBTIQA+ users on dating apps. For example, in-app tools designed to reduce anxiety or support users facing cyberbullying could enhance user experience and well-being. By expanding upon these insights, future research can contribute to a nuanced understanding of digital behaviors within the LGBTIQA+ community and support the development of digital interventions that create healthier, more supportive online spaces.

Lastly, while this study focuses on LGBTIQA+ users, its findings hold broader implications for other vulnerable populations. Researchers could extend this work to explore similar dynamics within different marginalized groups, contributing to a more inclusive understanding of how psychological states affect diverse user experiences across digital platforms.

7. Limitations

This study has several limitations that should be considered when interpreting its findings. Firstly, the sample is limited to LGBTIQA+ users primarily from Croatia, Serbia, and Bosnia and Herzegovina. While this focus provides insight into a specific regional context, the cultural and social dynamics influencing digital dating experiences in these countries may not be fully representative of the broader LGBTIQA+ population. Consequently, the generalizability of the findings to LGBTIQA+ users in other regions or countries with different cultural and social environments may be limited. Future studies could address this limitation by including more diverse samples from various cultural and geographic backgrounds.

Secondly, the study relies on self-reported data collected through an online survey, which is subject to potential biases such as social desirability bias or recall bias. Participants may have underreported or overestimated certain experiences, particularly sensitive issues like cyberbullying, due to privacy concerns or discomfort. This reliance on self-reporting may affect the accuracy of the findings, especially regarding users’ mental health and emotional experiences on dating apps. Using additional methods, such as interviews or longitudinal designs, could help mitigate this limitation and provide more nuanced insights.

Another limitation is the cross-sectional design of the study, which captures user experiences and emotions at a single point in time. This design does not allow for observations of changes over time, limiting the ability to determine causality or how emotional responses and behaviors evolve with prolonged dating app usage. Longitudinal studies would be beneficial in exploring how users’ mental health and attitudes toward dating apps develop over extended periods, particularly in response to repeated interactions and potentially negative experiences like cyberbullying.

The study also focuses primarily on emotional and psychological constructs such as anxiety, fear, self-confidence, and security perceptions, without fully exploring other potential influencing factors, such as the role of specific app features, user interface design, or community support systems. These factors could also significantly shape users’ experiences and attitudes, especially within the context of LGBTIQA+ dating apps. Including these additional dimensions in future research would provide a more comprehensive understanding of the factors affecting user experience and engagement.

Finally, while this study provides valuable insights into the digital experiences of LGBTIQA+ individuals, it does not differentiate within this community by specific subgroups, such as gender identity, age, or sexual orientation. Variations within the LGBTIQA+ population, including the unique challenges faced by transgender, nonbinary, or bisexual users, may influence their experiences on dating apps differently. Future studies could benefit from segmenting participants by these characteristics to uncover any subgroup-specific dynamics and better address the diverse needs within the LGBTIQA+ community.

8. Conclusions

This study contributes to the growing field of research examining the impact of dating apps on the mental health and well-being of LGBTIQA+ individuals, revealing both positive and negative outcomes associated with their usage. Our findings highlight significant relationships between cyberbullying, perceived security, fear, self-confidence, and mental health-related constructs such as anxiety, mood, and stress. These results underscore the complex interplay of social and psychological factors that shape user experiences, especially within a community that often faces unique social pressures and discrimination. Specifically, the data indicate that while dating apps provide important spaces for connection and community building, they also expose users to risks that can exacerbate feelings of fear, insecurity, anxiety, and reduced self-confidence.

The implications of these findings suggest several directions for future research. Firstly, longitudinal studies are needed to capture how prolonged and evolving engagement with dating apps impacts users’ mental health over time. This approach would allow researchers to observe changes in psychological outcomes as users navigate different stages of app engagement, potentially adjusting to or intensifying their experiences of cyberbullying, security concerns, and self-perception. Secondly, it will be essential to increase demographic diversity in future samples. By incorporating a wider range of age groups, socioeconomic backgrounds, and geographic regions, researchers can better understand how cultural and societal factors may moderate or amplify the effects identified in this study.

Another promising avenue for future research is the investigation of specific intervention strategies aimed at mitigating the negative psychological impacts associated with dating app use. These could include the development of in-app tools that offer users access to mental health resources, support for reporting and addressing cyberbullying incidents, and enhanced privacy controls that allow users to customize their exposure levels according to personal comfort. Research on the efficacy of these interventions could inform dating app developers and help create a safer, more inclusive digital environment for vulnerable users.

Furthermore, qualitative research would complement these quantitative findings by exploring the nuanced, subjective experiences of LGBTIQA+ individuals on dating apps. Interviews, focus groups, and thematic analyses could provide deeper insights into how users perceive and navigate challenges related to self-confidence, safety, and community connection. This approach would enrich the understanding of emotional and psychological responses that quantitative data alone may not fully capture, thereby offering a more holistic view of the digital dating experience within this population.

Finally, it would be valuable for future studies to examine how external social and technological changes influence the relationship between dating app usage and mental health. For example, shifts in social norms, policy changes related to online harassment, or advancements in data security technology could significantly impact user perceptions of safety and social interaction online. Understanding these broader contextual factors could inform future strategies to support user well-being, both by adapting app features and by guiding policy-making efforts to protect vulnerable communities in digital spaces.